Improving Code Readability With Functions And Descriptive Names
Displaying images with various types of annotations using matplotlib. The `show_images` function takes in a dataset and displays images along with their corresponding annotations, customizable to attribute, identity, bounding box or landmark data.
Buy Me a Coffee☕ *My post explains CelebA. CelebA() can use CelebA dataset as shown below: *Memos: The 1st argument is root(Required-Type:str or pathlib.Path). *An absolute or relative path is possible. The 2nd argument is split(Optional-Default:"train"-Type:str). *"train"(162,770 images), "valid"(19,867 images), "test"(19,962 images) or "all"(202,599 images) can be set to it. The 3rd argument is target_type(Optional-Default:"attr"-Type:str or list of str): *Memos: "attr", "identity", "bbox" and/or "landmarks" can be set to it. An empty list can also be set to it. The multiple same values c...